Evaluating artificial intelligence in the diagnosis of hip fractures: an analysis of sensitivity, specificity, positive and negative predictive values, and accuracy

Mads Hoelgaard Christensen, Rasmus Elsoe, Firaz Mahdi, Mate Hever, Sara Arif-Miscov, Peter Larsen

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DOI
10.1007/s00256-026-05370-5
Published
2026-09-14
Container
Skeletal Radiology
Publisher
Springer Science and Business Media LLC
Open access
unknown

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BibTeX

@article{allodium:10.1007/s00256-026-05370-5,
  title = {Evaluating artificial intelligence in the diagnosis of hip fractures: an analysis of sensitivity, specificity, positive and negative predictive values, and accuracy},
  author = {Mads Hoelgaard Christensen and Rasmus Elsoe and Firaz Mahdi and Mate Hever and Sara Arif-Miscov and Peter Larsen},
  year = {2026},
  journal = {Skeletal Radiology},
  doi = {10.1007/s00256-026-05370-5},
  url = {https://doi.org/10.1007/s00256-026-05370-5}
}

RIS

TY  - JOUR
TI  - Evaluating artificial intelligence in the diagnosis of hip fractures: an analysis of sensitivity, specificity, positive and negative predictive values, and accuracy
AU  - Mads Hoelgaard Christensen
AU  - Rasmus Elsoe
AU  - Firaz Mahdi
AU  - Mate Hever
AU  - Sara Arif-Miscov
AU  - Peter Larsen
PY  - 2026
JO  - Skeletal Radiology
DO  - 10.1007/s00256-026-05370-5
UR  - https://doi.org/10.1007/s00256-026-05370-5
ER  - 

APA

Christensen, M. H., Elsoe, R., Mahdi, F., Hever, M., Arif-Miscov, S., & Larsen, P. (2026). Evaluating artificial intelligence in the diagnosis of hip fractures: an analysis of sensitivity, specificity, positive and negative predictive values, and accuracy. Skeletal Radiology. https://doi.org/10.1007/s00256-026-05370-5

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